Mobile Apps, Trading Behaviors, and Portfolio Performance: Evidence from a Quasi-Experiment in China

Che-Wei Liu (), Sunil Mithas (), Yang Pan () and J. J. Po-An Hsieh ()
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Che-Wei Liu: W. P. Carey School of Business, Arizona State University, Tempe, Arizona 85287
Sunil Mithas: Muma College of Business, University of South Florida, Tampa, Florida 33620
Yang Pan: A.B. Freeman School of Business, Tulane University, New Orleans, Louisiana 70118
J. J. Po-An Hsieh: Robinson College of Business, Georgia State University, Atlanta, Georgia 30303

Information Systems Research, 2025, vol. 36, issue 2, 828-846

Abstract: Mobile apps are among the most important and widely used financial technology (fintech) innovations in the brokerage industry. Surprisingly, despite their increasing economic importance and theoretical significance, few studies examine the effects of mobile app use on individual investors’ financial decisions and performance. This study seeks to understand how mobile apps influence investors’ trading behaviors and portfolio performance by using a proprietary longitudinal data set from December 2012 to November 2015 from a large securities company in China with a quasi-experimental setting to answer our research questions. We leverage the introduction of an app to identify the effect of mobile app adoption by using a sample of 20,665 investors. We use the generalized synthetic control method and find that mobile app adoption does not affect investors’ portfolio performance when one examines aggregate impacts using a binary indicator of mobile app use. Our analyses of the mechanisms indicate that adopting mobile apps results in a noticeable decrease in time constraints, a proxy for transaction friction, and a modest increase intrend-chasing bias, reflecting tendencies toward myopic decision making. Because the reduction in time constraints can benefit investors’ performance, the increase in trend-chasing can be detrimental to investors’ performance; our findings explain why mobile app adoption has no overall effect on portfolio performance. Further analyses of adopters’ postadoption behaviors provide interesting insights and show that the mobile app usage intensity has an inverted U–shaped relationship with portfolio performance. The results are robust to using different samples or excluding high market volatility periods and by using a variety of methods, such as propensity score matching, dynamic matching, stacked difference in differences, or an instrumental variable approach. We discuss the implications for research and practice.

Keywords: financial technology; fintech; mobile apps; generalized synthetic control; difference in differences; quasi-natural experiment; portfolio performance (search for similar items in EconPapers)
Date: 2025
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